Components Of Hybrid Electric Vehicles Research Articles

Research on car-following control and energy management strategy of hybrid electric vehicles in connected scene

To address the comprehensive optimization problem of driving performance and fuel economy in the driving process of hybrid electric vehicles (HEV) in the car-following scene in the connected environment, an energy management strategy (EMS) based on front vehicle speed prediction and ego vehicle speed planning is designed by combining intelligent transportation system (ITS) technology. The front vehicle speed predictor is first established based on the long short-term memory neural network (LSTM). Then, based on the predicted speed of the front car, the predictive cruise control (PCC) strategy is designed for realizing the speed control in the car-following scene by combining it with the adaptive cruise control (ACC). Finally, based on the planned vehicle speed, deep reinforcement learning (DRL)-based EMS is used to optimize the power distribution among different power components of HEVs. The analysis of simulation results under the SUMO-Python joint simulation platform verifies the proposed strategy.

Performance of hybrid electric vehicle air-conditioning using SiO2/POE nanolubricant

The automobile air-conditioning (AAC) system uses the most energy among all auxiliary components in hybrid electric vehicles (HEV) with an electrically-driven compressor (AAC-EDC). Incorporating nanolubricant improves AAC-EDC performance and reduces battery and AAC component size. This study aims to assess the performance of an AAC-EDC system by employing SiO2/POE nanolubricants. The performance of the AAC-EDC was examined using SiO2/POE with a volume concentration of up to 0.01 %, a refrigerant charge of 120–160 g, and a compressor speed of 1200–3840 rpm. The performance of the AAC system was measured by its heat absorption, compressor work, coefficient of performance (COP), and EDC power consumption. The SiO2/POE was stable for 30 days with a zeta potential of 102.5 mV. The SiO2/POE demonstrated superior performance over the pure POE lubricants. The compressor work and power consumption were reduced to 26.17 % and 11.97 %, respectively. The lowest expansion valve discharge temperature of 9.6 °C was achieved at 160 g refrigerant charge and compressor speed of 3840 rpm. The nanolubricant attained the highest COP of 3.36 at 1860 rpm speed and 160 g charge. The SiO2/POE nanolubricant with a volume concentration of 0.01 % is highly recommended for optimal performance in the AAC-EDC system.

WITHDRAWN: Sensitivity analysis of boundary conditions on a series hybrid electric vehicle components through the artificial neural network

WITHDRAWN: Sensitivity analysis of boundary conditions on a series hybrid electric vehicle components through the artificial neural network

Numerical Comparison of Driving Cycles with Different Electric Motors (IM and PM) Operated in a Hybrid Electric Vehicle

The motor / generator instrument, which is the one of the key important components of hybrid electric vehicles, influence vehicle efficiency and emission scale with its types and features. For that reason, the electric motor (electric machine-EM) selection and identification are playing a crucial role. In this simulation study, effects of two different motors, Induction and Permanent Magnet (IM and PM) to emission and performance were compared for two driving cycles (FTP75 and NEDC) on a serial configuration hybrid electric vehicle which modeled with AVL Cruise. The general purpose of the work is, selecting electric motors that they have same output powers although the rotational speeds are different; and modeled for the same vehicle and identifing the effects of different driving cycles on the vehicles were compared. HEVs performance and emission results illustrated and electric machines performances and efficiency maps are graphically charted. Overall performance and emission outputs for two different driving cycles are discussed detailed. Also, a general concluded summary table that related the performance and emission outputs of different machines usage is presented. As a result, according to these modeling and test results, PM motor is more efficient than IM motor on overall simulation results, especially decreases the emission values at high speeds.

Generic power split modelling for compound epicyclic four-speed gears

Power split devices designed as compound epicyclic four-speed gears are essential components of Hybrid Electric Vehicles both for passenger cars and heavy-duty trucks. There are numerous studies regarding power split models or numerical analyses including state variable choice and model variants. However, different approaches for each gear type are the typical procedure. So it is of generic and urgent interest to overcome diverse parameter definitions and various dynamical models. Generic modelling based on three shafts and numerical power ratio analyses specific to one special four-shaft gear were introduced. The key idea of this paper is to upgrade and generalize these approaches to any four-shaft devices. The objective is one generic power flow model and a generic power ratio research based on generic parameter definitions. Unified parameter sets based on gear construction and geometry assure easy customization and any choice of state variables. Two standard gears, three passenger car gears and one innovative device serve as examples. Gear comparison studies get more comprehensible. This paper applies Bond Graphs. Other power flow representations can be utilized for unified approach suggested as well.

Reducing the variability of hybrid electric vehicle fuel economy in the real world

Apart from improving the fuel economy, a reduction in the variability of the fuel economy is also of significant importance for hybrid electric vehicles. Previously, research on how to optimise the sizes of the powertrain components of hybrid electric vehicles has generally focused on improving the fuel economy over a given driving pattern. The variability of the fuel economy over a realistic range of driving patterns has generally been overlooked, and this can mean that the fuel economy benefits of hybrid electric vehicles are not consistently realised in real-world usage. In a recent study, a new methodology for design optimisation of the powertrain components of hybrid electric vehicles was proposed for the reduction in the variability of the fuel economy due to variation in the driving patterns, but the methodology needs to be validated in real-world usage for practical applicability. In this paper, the methodology is validated in real-world driving conditions. This paper investigated the methodology for 10 real-world driving patterns generated by 10 different drivers over a predefined route consisting of urban and highway driving. The study was carried out using a simulation model of a Toyota Prius hybrid electric vehicle which was considered as the benchmark vehicle. The design produced by the methodology reduced the variability of the fuel economy by 5.3% without reducing the average fuel economy compared with the Toyota Prius over the 10 real-world driving patterns. This demonstrates that the methodology described is applicable to real-world usage.

Rare earth element recovery potentials from end-of-life hybrid electric vehicle components in 2010–2030

Increasing attention is currently given to the management of end-of-life (EoL) hybrid electric vehicles (HEVs), because approximately two decades have passed since they were first introduced to the market. A HEV would be one of the largest consumers of rare earth elements (REEs), and hence represents the greatest potential for REE recovery in the future. The purpose of this study is to clarify the present and future recovery potential of REEs that are disposed of as EoL HEVs. This study first estimated the numbers of EoL HEVs during fiscal years (FYs) 2010–2030, and then clarified the potential for recovery of REEs from two HEV-specific components—the hybrid transmission and NiMH battery unit. The results suggest that 0.51–0.65 million HEVs will reach the EoL stage in FY2030, compared with only 11,000 HEVs in FY2010. As of FY2030, REE recovery potentials will increase to 220 tons and 2900 tons for EoL hybrid transmission and NiMH battery units, respectively. A total of 49,000 tons of REEs will be contained within HEV-specific components of HEVs still in use. Moreover, the potential for recovery of REEs from EoL hybrid transmissions and NiMH battery units is estimated to equal 35.4 and 92.1 % of respective demand.

An applied methodology for multi-objective optimum sizing of hybrid electric vehicle components

In recent years, automobile industry focuses on the reducing the imperfections of hybrid electric vehicles (HEVs), such as higher cost, added weight of batteries, limited range, recharging facilities and emission rates. In the view of the related studies, we can infer that fuel cell (FC)-Battery hybrid configuration is a viable alternative solution. Such that, FCs are eco-friendly and proper for long ranged drives, on the other hand batteries have fast response for varying power demands. Moreover, FC-Battery hybrid electric vehicle (FCBHEV) proposes solutions for the imperfections. So, we deal with optimal sizing of FCBHEV and propose a methodology for the optimization of HEV components using the multi-objective approach considering the minimization of operating cost, weight and volume simultaneously. To optimize the sizing of HEV components, the mixed integer linear programming (MILP) model is tested in GAMS v.24.1.3 using the solver CPLEX v.12 and optimization processes are performed for different range of drive cycles and the results are discussed to reveal the effectiveness of the approach.

A Systematic Way of Choosing the Components of HEV and Optimization of Power Management Strategy for Real City Driving Condition

To improve the fuel economy of Hybrid Electric Vehicles (HEVs)，it is necessary to propose a framework which contains choosing the driveline structure, sizing components and optimizing the control strategy. By analyzing the operating character of the bus through the data from real road we find out the suitable components in the HEV driveline. Then the simulation models are built up. The PNGV systems analysis toolkit (PSAT) models are used to simulate the HEV. Subsequently optimization is performed to achieve the minimum fuel consumption. Finally the optimized parameters which mainly consider the engine start power, the engine operating area are found. The bench test results prove that the methods that we use are available.

Design for Motor Controller in Hybrid Electric Vehicle Based on Vector Frequency Conversion Technology

Motor and its control technology are one of the main components of Hybrid Electric Vehicle (HEV). To meet HEV's fast torque response, vector control algorithm based on rotor flux-oriented and simulation model is concerned and modular designs for controller's hardware and software are presented in the paper in order to build a platform to achieve the vector control of asynchronous induction motor. Analyze the controller's electromagnetic compatibility, introduce the corresponding antijamming measures to assure the normal operation of the electromagnetic sensitive devices such as CAN bus; experiment proves that the measure is practical and feasible. On the basis of the control logic correct, such as improving CAN bus communication reliability, assuring power-on sequence and fault treatment, carry on the motor bench experiment, test its static properties, and adjust the controller parameters. The experimental results show that the designed driving system has the performance of low speed and high torque, a wide range of variable speed and high comprehensive efficiency.

Battery and battery management for hybrid electric vehicles: a review

According to the legal, social and economic requirements for improved road transportation hybrid electric vehicles (HEVs) are one of the most intensively investigated vehicle concepts of today. To exploit their potential for emission reduction and performance improvement the energy storage system has to be considered as one of the key components of HEVs. This paper reviews the present state of the art pointing out advantages and drawbacks for each battery technology relevant for HEV application. Moreover, it describes the main constrains and requirements from the battery management's point of view. The tools usually applied by battery system developers are covered as well as the processes for identification and design of the optimal battery pack and the appropriate battery management. Finally, the main adjustments that are necessary for customizing a basic battery management system for a given battery chemistry are discussed.

Simulation-based optimal sizing of hybrid electric vehicle components for specific combat missions

The US Army and the Defense Advanced Research Projects Agency (DARPA) are currently supporting the development of conceptual military vehicle designs capitalizing on maturing technologies associated with hybrid electric vehicle propulsion and advanced electrical loads. Preliminary trade studies associated with these concepts often focus on determining the "best" mix of power system components to achieve the desired performance levels at a minimum overall impact on the vehicle. This paper describes an approach to this optimization through the use of vehicle performance simulation. By using simulation, one can address the complex relationship between the mission needs and the required subsystem performance in a dynamic environment. Results for three fictional mission sequences are provided to show how simulations can be used to insure that complex performance goals are met with minimum subsystem sizes. These minimum sizes can then form a baseline for further sizing constraints based on arrangements, availability, and other design considerations while minimizing overall design.